The Control Systems Engineering for Optimizing a Prenatal Weight Gain Intervention is an ongoing prospective, trial that uses a two-staged approach to develop an individually tailored (just in time) intervention (Healthy Mom Zone) that adapts to the unique needs of each overweight and obese pregnant woman (OW/OBPW) to manage GWG. Capitalizing on the infrastructure and intensive data collection as part of Healthy Mom Zone, the proposed research adds three major pieces by collecting indicators of fetal growth, postpartum weight and infant weight across the first year of life. Specifically, this innovative research has proposed the following aims: a) prospectively characterize the crossover effects of our adaptive GWG intervention on fetal growth, postpartum maternal weight, and infant obesity risk, (b) determine how individual differences in infant oral/gut microbiome, sleep duration, stress and feeding practices increases susceptibility to childhood obesity, and (c) use principles of engineering to extend, refine, and validate dynamical systems models that characterize fetal growth, infant weight, and maternal postpartum weight. The obesity epidemic is a major public health concern affecting all age groups. Half of all pregnant women in the U.S. begin their pregnancies overweight or obese with 60% of these women exceeding the gestational weight gain (GWG) recommendations; an independent predictor for the onset of obesity, type 2 diabetes, and cardiovascular diseases among women and their offspring. The prenatal period is an opportune time to intervene and break the intergenerational cycle of obesity by reducing fetus exposure to an obesogenic intrauterine environment through promoting maternal energy balance. We hypothesize that the Healthy Mom Zone GWG intervention will create a healthy intrauterine and postnatal food and physical activity environment with sustainable effects (i.e., carry-over effects of the intervention) on maternal postpartum weight and infant obesity risk. Our team has already conceptualized and used control systems engineering principles and dynamical modeling approaches to develop a fetal intergenerational fetal energy balance model. We will expand the fetal growth model by developing and validating a model that considers how several individual characteristics (e.g., maternal-infant sleep, temperament, parent feeding practices, and maternal stress) interact with indicators of the intrauterine and postnatal environment (eating and physical activity) to affect postpartum maternal and postnatal infant weight up to one-year post-delivery. This application has several unique features/strengths including: public health/clinical significance, dynamical systems modeling of the mother-infant dyad to prevent obesity and cardiovascular disease, modeling and CSE to build and optimize the adaptive intervention, and exploration of the development of the microbiome. This research compliments the over-reaching goal of NIH to improve maternal/infant health and it is consistent with NHLBI's mission to promote research to reduce the burden of heart, lung, and blood diseases and their related comorbidities worldwide.